Conduct statistical analyses to support business decisions. Serve as a resource to shape future directions in data science and analytics across the district. Develop interactive reporting, data visualizations, and other software to support business needs. Analytics activities include prediction of electrical demand and employee turnover, assessment of equipment reliability and operational risk due to weather or changing environmental conditions, and modeling of employee compensation and completion time for mission-critical scheduling tasks.

Develop an internal training process for data science, leveraging online resources and cooperative learning groups to allow professionals to learn R, data visualization using ggplot2, data cleaning using the tidyverse, reporting using rmarkdown, basic statistical modeling and machine learning techniques while integrating those skills into their current position responsibilities.

Part-time position Mar-2018 to present.

Develop web applications to present data and statistical analyses to targeted groups. Examples:

• Soybean Planting Decision Tool developed for the Cropping Systems Lab at Iowa State
• Late-Season Nitrogen Deficiency Risk Tool developed for the Iowa Soybean Association